Application of a large-scale electricity storage system including secondary batteries is expected for suppressing fluctuation of a power generation that utilizes natural energy, such as solar light or wind power, suppressing fluctuation of a power demand, and shifting a peak. In order to enable an operation that accomplishes the maximum performance in such a large-scale electricity storage system, it is important to precisely grasp the characteristic of the secondary battery (hereinafter, also simply referred tows “battery”) at a given time point, i.e., the status like a capacity and an internal resistance.
Several schemes have been already proposed to estimate the capacity of the battery and the internal resistance thereof with the system being in an operated status. For example, a method of obtaining an open circuit voltage by calculation based on the closed circuit voltage, the current, and the temperature to obtain a State Of Charge (SOC, battery remaining level), and calculating the battery capacity by utilizing a correlation and an extrapolation, and a method of obtaining an internal resistance by parameter identification using a model and by learning under various conditions are known.